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The query asks the model to recall the topic of an earlier conversation about Tesla; the gold answer is anchored in one specific session about Pooja’s dig site
from the top result below

Report GitHub Issue

https://arxiv.org/html/2608.02613v1
We evaluate five open-weight readers with Vanilla context, BM25-RAG, Oracle retrieval, Memobase, and MemSearch as memory backends

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

Artificial Intelligence

https://arxiv.org/list/cs.AI/new
We demonstrate that it can self-assemble functional circuits from scratch and rapidly re-route logic around permanent, previously unseen hardware faults

1 Introduction

https://arxiv.org/html/2501.13956v1
2 Knowledge Graph Construction 2.1 Episodes 2.2 Semantic Entities and Facts 2.2.1 Entities 2.2.2 Facts 2.2.3 Temporal Extraction and Edge Invalidation 2.3 Communities 3 Memory Retrieval 3.1 Search 3.2 Reranker 4 Experiments 4.1 Choice

Report GitHub Issue

https://arxiv.org/html/2608.03048v1
for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates can overwrite early critical evidence with later irrelevant content, and serial inter-chunk dependencies limit parallelism and cause latency to increase with context length

Cryptography and Security

https://arxiv.org/list/cs.CR/new
fewer | more | all New submissions (showing 32 of 32 entries) [1] arXiv:2608

Software Engineering

https://arxiv.org/list/cs.SE/new
Yet it remains unclear when further evolution helps, how successful and failed trajectories shape revision, and whether extra test-time computation can recover the same gains

Report GitHub Issue

https://arxiv.org/html/2609.03027v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

Report GitHub Issue

https://arxiv.org/html/2609.02852v1
Report GitHub Issue Description: arXiv is now an independent nonprofit

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https://arxiv.org/pdf/2407.00225
-scale, Independent and Comprehensive study of the power of LLMs for test case generationWendkûuni C. OuédraogoKader KaboréYinghua LiHaoye TianAnil KoyuncuJacques KleinDavid LoTegawendé F. Bissyandéhttp://creativecommons.org/licenses

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https://arxiv.org/src/2608.03883
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https://arxiv.org/src/2608.04003
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https://arxiv.org/src/2006.02893
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https://arxiv.org/src/2006.03271
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https://arxiv.org/pdf/2211.01910
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https://arxiv.org/pdf/2006.04122
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https://arxiv.org/src/2211.01910v2
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https://arxiv.org/src/2006.02464
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Condensed Matter

https://arxiv.org/list/cond-mat/new
The mixed anomaly between these is accommodated by the not-on-site action of the symmetries

Report GitHub Issue

https://arxiv.org/html/2607.22511v2
A statement can be free of sorry and still be mathematically uninformative: a definition may reduce to True; or an unproven step may be introduced as an axiom that the kernel accepts

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https://arxiv.org/pdf/2608.03014
Á‡ûïo*6Ñer�ìfÃÌò™™ïÎR0� 80bƒÜå`ƒm À‡ pÀqMp�˜Œã„�FqA�p7À׿¸Fáà`q©øqwÆ$«‹ :4`DÁøq¶-Ë�—SWËÊ ÆÅþ†x­òò°á"Q FPëÆ{ËŽ@q�îÓ¢~=–ŸMuĿۭQ˜}ÛpŒäôÒüý,ÀXáHpªÒC‰Ûèà´«ó÷–fSæÍ[ n»×ý½»šmæËÝÈ‹’­s�Ã8¦„C(éÇqõ8–'Œý‡èYÊ]Täå¼ÉÞ{óg[ b«Clö

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https://arxiv.org/pdf/2608.01785
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Computation and Language

https://arxiv.org/list/cs.CL/new
LG) Half a million cuneiform clay tablets survive in museums worldwide, yet modern users can neither read nor write in the world's oldest writing system, leaving a 4,000-year cultural barrier that existing NLP tools have only partially addressed

[2608.03860] SciRet: A Compute-Aware Empirical Study of Retrieval and

https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation

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https://arxiv.org/pdf/2210.00282
}ûîj%à'ãL,í®VÚ¿]üúpuý–‹]•9Ëw‡û]ÂãHä|——"JR±;Ô»‚÷1�ß3–ÞîC–ÄÁç=ü'û wI0i¢å¤+Ú�'£¿‘“;çxwzjˆw¯TG´æÔ?˜ó>çA´q·epkò¹\Vïÿ=¼»~›Ç«·²„E™(w1½ò°/Y ïÔ$Û°W$a[–Ei&¼øsFÁù]Èxp:L’¨äœN®,-„·´È½¥@ûì(ÎR¤,êag}|%§ s£}˜±8øíaÀ®-üI””ùw£„ìçz�Ï@UøM8»P

Statistics Theory Mar 2024

https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other] Title: Warped Kernel Estimator for I

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

https://arxiv.org/html/2508.20101v1
The model combines classical GARCH(pp, qq) dynamics with spatially correlated innovations and spatially varying parameters, estimated using local likelihood methods

[2608.12700] A Contract-Grade Verifier for LLM-Generated GPU Kernels

https://arxiv.org/abs/2608.12700
A kernel can pass that test and still be silently wrong

Stabilization of First-Order Partial Integro-Differential Equations with

https://arxiv.org/html/2608.02851v1
org perpetual non-exclusive license arXiv:2608

[2204.04218] Multimodal Multi-Head Convolutional Attention with Various

https://arxiv.org/abs/2204.04218
In many situations, computed tomography (CT) or magnetic resonance imaging (MRI) techniques capture several scans (modes) during a single investigation, which can jointly be used (in a multimodal fashion) to further boost the quality of super-resolution results